Posts Tagged ‘social network’

How to split up the US (Pete Search)

Tuesday, February 16th, 2010

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[Editor's note: Topology analysis of the Facebook social network (how many people in one town are connected to another) overlayed on a curious map base in geographic and regrouped into regions like Greater Texas, Socalistan, and Mormonia. Not quite sure of how the author define's Pacfiica and the map suffers from poor red-green contrast but cool concept.]

Republished from Pete Search.

As I’ve been digging deeper into the data I’ve gathered on 210 million public Facebook profiles, I’ve been fascinated by some of the patterns that have emerged. My latest visualization shows the information by location, with connections drawn between places that share friends. For example, a lot of people in LA have friends in San Francisco, so there’s a line between them.

Looking at the network of US cities, it’s been remarkable to see how groups of them form clusters, with strong connections locally but few contacts outside the cluster. For example Columbus, OH and Charleston WV are nearby as the crow flies, but share few connections, with Columbus clearly part of the North, and Charleston tied to the South:

Columbus Charleston

Some of these clusters are intuitive, like the old south, but there’s some surprises too, like Missouri, Louisiana and Arkansas having closer ties  to Texas than Georgia. To make sense of the patterns I’m seeing, I’ve marked and labeled the clusters, and added some notes about the properties they have in common.

Continue reading at Pete Search . . .

News Dots (Slate)

Wednesday, September 9th, 2009

slatenewsdots

[Editor’s note: This is one of the first tools I’ve seen that links topics, people & places into a network of graduated circles based on their ranking in the news. The circles are arranged based on their edge connections within the overall topology using the Flare visualization package in Flash AS3. As seen in the above screenshot, Germany is linked to Afghanistan, NATO, the Taliban, The Washington Post, and 20 other nodes. This project is one step forward in the vision I outlined in Topology and Projections: 21st Century Cartography. Disclosure: Slate is owned by the Washington Post Company, my employer, but I was not involved in this project.]

Republished from Slate.

Introducing News DotsAn interactive map of how every story in the news is related, updated daily.

Like Kevin Bacon’s co-stars, topics in the news are all connected by degrees of separation. To examine how every story fits together, News Dots visualizes the most recent topics in the news as a giant social network. Subjects—represented by the circles below—are connected to one another if they appear together in at least two stories, and the size of the dot is proportional to the total number of times the subject is mentioned.

Like a human social network, the news tends to cluster around popular topics. One clump of dots might relate to a flavor-of-the-week tabloid story (the Jaycee Dugard kidnapping) while another might center on Afghanistan, Iraq, and the military. Most stories are more closely related that you think. The Dugard kidnapping, for example, connects to California Gov. Arnold Schwarzenegger, who connects to the White House, which connects to Afghanistan.

To use this interactive tool, just click on a circle to see which stories mention that topic and which other topics it connects to in the network. You can use the magnifying glass icons to zoom in and out. You can also drag the dots around if they overlap. A more detailed description of how News Dots works is available below the graphic.

Interact with the original and learn more at Slate . . .

Social Networks’ Sway May Be Underestimated (Washington Post)

Thursday, May 29th, 2008

[Editor’s note: Graphic shows not physical geography but a topological network of social friendships and how smokers used to be at the center of social networks but are now more isolated. If someone becomes a smoker than it cascades thru the social network, but if someone quits smoking, it can have a similar effect by influencing others in the crowd to quit. The program used to make the graphic is called Pajek. Thanks Patterson!]

smokers quiting social network wash post

Reprinted from The Washington Post. By Rob Stein, Staff Writer. Monday, May 26, 2008.

Facebook, MySpace and other Web sites have unleashed a potent new phenomenon of social networking in cyberspace. But at the same time, a growing body of evidence is suggesting that traditional social networks play a surprisingly powerful and underrecognized role in influencing how people behave.

The latest research comes from Nicholas A. Christakis, a medical sociologist at the Harvard Medical School, and James H. Fowler, a political scientist at the University of California at San Diego. The pair reported last summer that obesity appeared to spread from one person to another through social networks, almost like a virus or a fad.

In a follow-up to that provocative research, the team has produced similar findings about another major health issue: smoking. In a study published last week in the New England Journal of Medicine, the team found that a person’s decision to kick the habit is strongly affected by whether other people in their social network quit — even people they do not know. And, surprisingly, entire networks of smokers appear to quit virtually simultaneously.

Taken together, these studies and others are fueling a growing recognition that many behaviors are swayed by social networks in ways that have not been fully understood. And it may be possible, the researchers say, to harness the power of these networks for many purposes, such as encouraging safe sex, getting more people to exercise or even fighting crime.

“What all these studies do is force us to start to kind of rethink our mental model of how we behave,” said Duncan Watts, a Columbia University sociologist. “Public policy in general treats people as if they are sort of atomized individuals and puts policies in place to try to get them to stop smoking, eat right, start exercising or make better decisions about retirement, et cetera. What we see in this research is that we are missing a lot of what is happening if we think only that way.”

For both of their studies, Christakis and Fowler took advantage of detailed records kept between 1971 and 2003 about 5,124 people who participated in the landmark Framingham Heart Study. Because many of the subjects had ties to the Boston suburb of Framingham, Mass., many of the participants were connected somehow — through spouses, neighbors, friends, co-workers — enabling the researchers to study a network that totaled 12,067 people.

When researchers analyzed the patterns of those who managed to quit smoking over the 32-year period, they found that the decision appeared to be highly influenced by whether someone close to them stopped. A person whose spouse quit was 67 percent more likely to kick the habit. If a friend gave it up, a person was 36 percent more likely to do so. If a sibling quit, the chances increased by 25 percent.

A co-worker had an influence — 34 percent — only if the smoker worked at a small firm. The effects were stronger among the more educated and among those who were casual or moderate smokers. Neighbors did not appear to influence each other, but friends did even if they lived far away.

“You appear to have to have a close relationship with the person for it to be influential,” Fowler said.

But the influence of a single person quitting nevertheless appeared to cascade through three degrees of separation, boosting the chance of quitting by nearly a third for people two degrees removed from one another.

“It could be your co-worker’s spouse’s friend or your brother’s spouse’s co-worker or a friend of a friend of a friend. The point is, your behavior depends on people you don’t even know,” Christakis said. “Your actions are partially affected by the actions of people who are beyond your social horizon” — but in the broader network.

In addition, the researchers found that the size of smokers’ own networks did not change over time, even though the overall number of smokers plummeted, from 45 percent to 21 percent of the population during that time. The researchers realized that what happened was that entire networks of smokers would quit almost simultaneously.

Continue reading . . .